一种基于纠错码的数字指纹方案

数字指纹技术是一种用来辨认非法拷贝，追踪非授权用户的新技术。它由嵌入拷贝各自不同的数据组成。现在，数字指纹已发展成为版权保护的一种重要手段。但一个问题也随之出现：对于数字指纹，可以通过比较找到它们的不同之处，于是一些用户可以通过合谋找到数字指纹的位置，更改数字指纹来隐匿自己。所以设计指纹算法的关键问题是如何防范合谋攻击。在这里，介绍了一种新的基于纠错码的数字指纹，并进一步分析了这种方案的性能。     

一种非线性的数字指纹合谋攻击方法

数字指纹是一种保护多媒体数字产品防止未授权用户使用的技术。目前,针对数值指纹的一种强大的攻击方法是合谋攻击。合谋者将各自的拷贝联合起来,通过移除或消减拷贝中原始指纹构建一个新的非法拷贝。以独立同分布的高斯指纹为研究对象,提出了一种新的非线性合谋攻击方法。该方法通过选取拷贝序列中各位置的最大值与最小值以及平均值,将最大最小值相加后减去平均值的方法产生出一个新的非法拷贝。结果显示该攻击方法在同等的感知条件下,能够对高斯指纹获得更有效的攻击。     

一种扩展的抗合谋数字指纹方案

数字指纹技术是一种可以追踪到非法拷贝源的数字版权保护技术,其中一种潜在的威胁就是几个合法用户共谋攻击。针对已有的抗合谋扩频正交数字指纹方案支持用户数较少的缺点,提出了一种关于扩频正交数字指纹码的扩展方案,从理论和实验上证明该方案提高了系统所能支持的用户数,并且保持了原方案较好的抗合谋性能。     

一种抗合谋攻击的数字指纹方案*

作为一种新型的数字版权保护技术,数字指纹通过在出售给每个消费者的数字拷贝中秘密地嵌入一个唯一的序列码来实现版权保护与盗版者追踪的目的。一旦发现未授权的数字拷贝时,内容提供商能够通过所提取到的序列码追踪到相应的盗版者。提出了一种多媒体指纹方案,其中IPP(identifi able parent property)码被用来构造消费者的序列码,以抵抗多个消费者之间的合谋攻击。实验结果表明,该方案具有较好的抗合谋性能。     

一种二进制数字指纹编码算法

抗合谋攻击是数字指纹技术中需要解决的关键问题之一.基于二进制随机编码,通过使用伪随机序列对指纹比特的重复嵌入进行控制,提出了一种有效的抗合谋攻击的数字指纹编码算法及其相应的跟踪算法.理论分析和实验结果表明,在适当的合谋尺寸下,该算法能够对非法分发者进行有效跟踪,同时无辜用户被诬陷的概率可以根据要求接近于0.由于在该算法中发行商无须知道用户原来的码字,因此可以说该算法是设计非对称指纹的一个很好的备选算法.     

一种基于随机码的多媒体数字指纹方案

如何抵抗多个用户的合谋攻击是设计数字指纹方案首要考虑的一个问题。论文提出了一种基于随机码的多媒体指纹方案,其中随机码被用来构造用户的指纹,以抵抗多个用户之间的合谋攻击。实验表明,该方案具有较好的抗合谋性能。     

扩频卷积指纹及其安全性分析

数字指纹是一种在每个数字作品拷贝中添加唯一性信息的版权保护技术.文中证明了扩频序列对组合、平均及噪声攻击具有有效的合谋容忍性质,并提出一种卷积码与扩频水印码相链接的安全指纹方法.译码方法也通过将备选子码集应用于Viterbi译码算法给予改进,进而合谋安全性和性能被分析与证明.结果表明该方法具有更短的码长和更快的叛逆者搜索性能.     

基于残留特征跟踪的抗合谋数字指纹

通过设计一种数字指纹的线性无关特征码,提出基于协同学的残留特征跟踪的抗合谋数字指纹,将协同学应用于数字指纹的合谋跟踪,建立了一套基于残留特征跟踪的抗合谋数字指纹方案.实验结果及分析表明,该方案能够在大幅度提高数字指纹的编码效率和跟踪效率的同时,基本上保证数字指纹的鲁棒性和抗合谋性.     

合谋安全的卷积指纹信息码

数字指纹是一种发行商通过在数字作品拷贝中添加唯一用户身份标记,使得能够识别出制作非法拷贝"叛逆者"的技术.目前,数字指纹方案中普遍存在着大用户数下指纹码构造过长以及无法有效叛逆跟踪的问题和缺陷.为了解决这些问题,在Boneh-Shaw的基础上,给出了指纹信息码的定义,并将卷积码与一般指纹码相结合,提出一种实际构造方法.同时,通过引入"备选子码集"的概念对Viterbi译码算法予以改进,给出了指纹信息码的译码算法.在理论与实例两方面对编码安全性质和性能的证明和分析结果均表明,所提出方案具有更短的用户信息编码长度,并实现了大用户集下有效叛逆用户的搜索.     

基于可再分发抗合谋编码的低失真水印方案

在大数据的时代背景下,数据潜在的价值使其成为重要的财富之一。数据的非法篡改、修正和非法分发给追踪数据的泄密源头带来巨大挑战。数字指纹技术可应用在数据泄密溯源领域,即在数据中嵌入一串能够唯一标识用户信息的序列,当数据发生泄密后,提取其中蕴含的数字指纹,追踪到泄密的叛逆者。多个用户对数据合谋攻击并泄密数据,从而毁坏其中嵌入的指纹信息达到逃脱追责的目的,抗合谋编码能够解决此问题。针对现有的数字指纹编码无法满足数据再分发需求、数字指纹嵌入造成较大数据失真的问题,本文使用BIBD（Balanced incomplete block design）作为外码,码字扩展后的C码作为内码,构建一种可再分发的抗合谋指纹编码RD-ACC（Redistributable anti-collusion fingerprint coding）。在此基础上,提出一种基于多目标优化的数据库指纹算法,能够在较小的数据库失真情况下保证数字指纹较高的鲁棒性,提取出的RD-ACC能够有效抵抗组内、组间多用户合谋攻击。实验结果表明,该算法能够在较小的数据失真下实现数据的再分发操作,并且能抵抗合谋攻击进行泄密溯源。     

Fingerprinting Compressed Multimedia Signals

Digital fingerprinting is a technique to deter unauthorized redistribution of multimedia content by embedding a unique identifying signal in each legally distributed copy. The embedded fingerprint can later be extracted and used to trace the originator of an unauthorized copy. A group of users may collude and attempt to create a version of the content that cannot be traced back to any of them. As multimedia data is commonly stored in compressed form, this paper addresses the problem of fingerprinting compressed signals. Analysis is carried out to show that due to the quantized nature of the host signal and the embedded fingerprint, directly extending traditional fingerprinting techniques for uncompressed signals to the compressed case leads to low collusion resistance. To overcome this problem and improve the collusion resistance, a new technique for fingerprinting compressed signals called Anti-Collusion Dither (ACD) is proposed, whereby a random dither signal is added to the compressed host before embedding so as to make the effective host signal appear more continuous. The proposed technique is shown to reduce the accuracy with which attackers can estimate the host signal, and from an information theoretic perspective, the proposed ACD technique increases the maximum number of users that can be supported by the fingerprinting system under a given attack. Both analytical and experimental studies confirm that the proposed technique increases the probability of identifying a guilty user and can approximately quadruple the collusion resistance compared to conventional Gaussian fingerprinting.      

Optimal fingerprint scheme for video on demand using block designs

Video fingerprint is a mechanism to protect movie from the traitors and also have the capability to identify the traitors. The problem arises in video fingerprint when several traitors having the same copies of a movie with different fingerprints collude together. During the collusion the original fingerprints in the movie will be removed or attenuated. Due to this the traitors can illegally copy, duplicate, record or redistribute the movie without having legitimate permissions. To avoid illegitimate acts of the traitors, a new Video on Demand architecture is proposed in this paper. This new architecture combines the proxy caching mechanisms in the peer to peer network to support larger users group. A new video fingerprinting scheme is proposed for this architecture, which can strongly resist against collusion attacks from the traitors. To check the appropriateness of our scheme, we have analyzed some of the existing schemes. The appropriateness is analyzed in terms of efficiency, effectivity and performance. To evaluate the optimality of these schemes, we have carried out simulation for our architecture. The results from the simulation show the optimal outcome for our scheme than any existing schemes.     

一种基于同态公钥加密的遥感影像数字指纹方案

针对非对称指纹计算复杂性高以及带宽效率低的问题,提出了一种基于同态公钥加密的遥感影像非对称指纹方案。在该方案中,内容提供商通过DCT扩频置乱方法加密遥感影像,运用Bresson同态公钥加密来实现解密密钥的非对称分发,通过客户端解密含指纹的遥感影像拷贝,使不同的解密密钥能够生成不同的含指纹拷贝。方案中公钥加密算法并未直接加密遥感影像,由此降低了计算复杂性并提高了加密效率;同时因为内容提供商只需为多个消费者生成相同的指纹拷贝,通过多播传输将其分发给不同的消费者,因此降低了带宽需求。实验表明：在用户数量较大的情况下,该方案可以有效提高带宽效率及加密效率,能够显著降低数据服务器的计算负载,减少用户等待时间。     

数字指纹协议的研究与发展

一、引言随着电子商务的发展,以无形的数字格式作为多媒体产品的发布形式将成为Internet上的主流方式。但由于软件产品的易拷贝性,对软件产品(如JPEG、GIF图像,应用程序,各种文档等)的盗版就变得异常容易。从目前的技术研究来说,在开放环境下要严格防止非法使用者的侵权拷贝是不太可行的。主要的研究方向集中在如何有效地追查非法拷贝源,即发     

On the Assumption of Equal Contributions in Fingerprinting

With a digital fingerprinting scheme, a vendor of digital copies of copyrighted material marks each individual copy with a unique fingerprint. If an illegal copy appears, it can be traced back to one or more guilty pirates due to this fingerprint. A coalition of pirates may combine their copies to produce an unauthorized copy with a false, hybrid fingerprint. It is often assumed in the literature that the members of the collusion will make equal contributions to the hybrid fingerprint, because nobody will accept an increased risk of being caught. We argue that no such assumption is valid a priori, and we show that a published solution by SebÉ and Domingo–Ferrer can be broken by breaking the assumption.      

A simple fingerprinting scheme for large user groups

Digital fingerprinting is an emerging technology to protect multimedia data from piracy, where each distributed copy is labeled with unique identification information. In coded fingerprinting, each codeword of the anti-collusion code is used to represent a user’s fingerprint. In real-world applications, the number of potential users can be very large and hence, the used anticollusion code should be easy to construct and have as many codewords as possible. This paper proposes a simple coded fingerprinting scheme, where the anticollusion code is constructed with an identity matrix. The main advantage of our scheme is its simplicity, as a large number of fingerprints can easily be generated to accommodate a large number of users. To improve collusion resistance, some transformations are performed on the original fingerprint in the embedding phase and the corresponding inverse transformations are performed on the extracted sequence in the detection phase.     

一种新的二次分发数字指纹协议

现有的数字指纹协议主要基于Buyer-Seller模型，卖方拥有数字产品的原始拷贝，在数字产品中嵌入与买方相关的数字指纹，出售给买方。如果卖方发现了非法拷贝，根据提取出的指纹跟踪非法的买方。该文介绍了有别于Buyer-Seller模型的二次分发模型，在此模型基础上，引入防篡改硬件和对称嵌入技术，提出了一种可用于在线交易的、安全高效的数字指纹协议。     

数字指纹技术研究进展

本文对数字指纹技术的应用及国内外的研究进展做了综述。首先简单介绍了数字指纹系统及其在版权保护 上的应用。然后分别介绍了传统的数字指纹技术,以及新型的基于多用户通信技术的指纹技术。指出了当前数字指纹技术存 在的不足,提出数字指纹技术今后的发展方向是以通信技术的角度作为切入点来研究对抗合谋攻击问题。     

Wi-Fi fingerprinting based on collaborative confidence level training

Wi-Fi fingerprinting has been a popular indoor positioning technique with the advantage that infrastructures are readily available in most urban areas. However wireless signals are prone to fluctuation and noise, introducing errors in the final positioning result. This paper proposes a new fingerprint training method where a number of users train collaboratively and a confidence factor is generated for each fingerprint. Fingerprinting is carried out where potential fingerprints are extracted based on the confidence factor. Positioning accuracy improves by 40% when the new fingerprinting method is implemented and maximum error is reduced by 35%.